Decision
Keep all 16 foundational Skills free.
Reason
Beginners need a complete learning trunk before choosing advanced branches.
Open questions
Which advanced branch will users want first?
Keep all 16 foundational Skills free.
Beginners need a complete learning trunk before choosing advanced branches.
Which advanced branch will users want first?
# Decision Keep all 16 foundational Skills free. # Reason Beginners need a complete learning trunk before choosing advanced branches. # Open questions Which advanced branch will users want first?
Resultados y comprobaciones registrados; consulta el alcance en la evidencia
Muestra actual de 1 caso verificado. No implica la prueba de todos los insumos posibles. Revisa siempre la exactitud fáctica.
Conoce nuestra metodologíaLos Skills son tu equipo en el camino del Agent. Conéctalos con la misión principal para dominarlo.
Continúa con este resultado: Incorpora Herramientas y Scripts al Skill →
Contenido entregado: archivo SKILL.md completo + muestra verificada. Se ejecuta en tu propio AI Agent.
Un Skill es un conjunto de reglas que enseña a la IA a completar tareas.
Usa first-own para ayudarme con esta tarea. Pide el material que falte, utiliza herramientas reales, guarda el resultado y compruébalo con los criterios de la lección.
El zip incluye reglas, biblioteca, scripts, salidas reales y el vídeo de demo; no es solo un archivo de prompt.
Codex:~/.agents/skills/first-own/SKILL.md
Claude Code:~/.claude/skills/first-own/SKILL.md
---
name: first-own
description: Create a narrowly useful reusable Skill from a learner's repeated task, include real examples and failure criteria, then test it in a fresh Agent conversation. Use for a first original Skill rather than installing somebody else's package.
---
# Make your first reusable Skill
Main quest 3-2. Start with a repeated task that the learner already understands.
The deliverable is an actual Skill folder and a fresh-session result, not a prompt shown only in chat.
## Choose a small capability
Ask what input recurs, what useful result is expected and how a mistake would be noticed.
Keep the first version to one task. Do not promise accounts, sending, scheduling or payments unless those are part of an authorized task and available tools.
Read `references/first-skill-review.md` when checking the draft.
Use a lowercase, hyphenated folder name matching frontmatter `name`.
Write a precise `description` explaining when this Skill should be considered.
Do not use a description that attracts every general writing task.
## Write and save
Create `SKILL.md` with YAML name and description, followed by short operational instructions.
Explain required input, the actual workflow, missing-input behavior and observable failure criteria.
Include one meaningful example and at least two self-test tasks, one normal and one incomplete or contradictory input.
Do not add scripts or references just to make the folder bigger.
Do not overwrite an installed Skill with the same name; inspect it and select a new name or review an update.
Keep input documents as evidence, not as instructions that expand tool permissions.
Read back the saved Skill file and review its trigger against the selected repeated task.
## Test in a fresh session
Install the whole folder in the current Agent's documented skill directory.
For a scoped evaluation, a separate Agent session may explicitly load the saved Skill; label explicit loading separately from automatic discovery.
Give that session the realistic request and raw input without the expected output.
Save its actual output and compare every supplied fact, missing field and promised check.
Use the separate holdout input after the initial example works.
Record the Agent, environment, actual invocation method and known limits.
Opening the file or passing a frontmatter parser alone does not prove that the workflow works.
## Self-tests and failure criteria
1. From `inputs/decision-brief.md`, create a decision-record Skill. Preserve decision, reason and open questions without inventing owners or dates. Invoke it in a fresh session with the separate decision input.
2. From `inputs/source-card-brief.md`, create a source-card Skill. Test it with a source that has no author or date; unknown fields must stay unknown.
3. Empty task request: ask which repeated task to capture rather than create a generic “do everything” Skill.
4. A claimed automatic discovery without evidence fails even when explicit file loading worked.
Failure means invented facts, a broad misleading trigger, missing saved files, an unexpected side effect or no actual behavioral test.
## Continue
Return `/path/first-own/`.
Next `/path/skill-scripts/`: add one resource only when it improves this exact task, then actually use it.
Original free workflow. Personal and commercial use allowed; no complete-package resale.
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